Proposes TD3-STEPD, a deep reinforcement learning method that distills several region-specific geomagnetic navigation policies into one student policy that generalizes to unseen simulated areas.
Promising aircraft navigation systems with use of physical fields: Stationary magnetic field gradient, gravity gradient, alternating magnetic field,
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Exploring the Generalizability of Geomagnetic Navigation: A Deep Reinforcement Learning approach with Policy Distillation
Proposes TD3-STEPD, a deep reinforcement learning method that distills several region-specific geomagnetic navigation policies into one student policy that generalizes to unseen simulated areas.